Community Blog What Is Big Data

What Is Big Data

This blog describes Big Data Definition, Feature, Structure, Application, and the development trend of Big Data.

Big data refers to a collection of data that cannot be captured, managed, and processed with conventional software tools within a certain time frame. Big data requires a new processing model to have stronger decision-making power, insight and discovery, and process optimization capabilities. It is a massive, high-growth, and diversified information asset.

Big Data Definition

Big data is a large-scale data collection that greatly exceeds the capabilities of traditional database software tools in terms of the acquisition, storage, management, and analysis. Big data has four characteristics: massive data scale, fast data flow, diverse data types, and low-value density.

The strategic significance of big data technology is not to master huge data information, but to professionally process these meaningful data. In other words, if big data is compared to an industry, the key to profitability of this industry is to improve the "processing capability" of data, and to achieve the "value-added" of data through "processing".

From a technical point of view, the relationship between big data and cloud computing is as inseparable as the front and back of a coin. Big data cannot be processed by a single computer, it must adopt a distributed architecture. It is characterized by distributed data mining of massive data. But it must rely on the distributed processing of cloud computing, distributed database and cloud storage, and virtualization technology.

With the advent of the cloud era, big data has also attracted more and more attention.
The analyst team believes that Big data is usually used to describe a large amount of unstructured data and semi-structured data created by a company. These data will spend too much time and money when downloaded to a relational database for analysis. Big data analysis is often associated with cloud computing, because real-time analysis of large data sets requires a framework like MapReduce to distribute work to tens, hundreds, or even thousands of computers.

Big data requires special technology to effectively process a large amount of data within a tolerable elapsed time. Technologies applicable to big data include massively parallel processing databases, data mining, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.

Big Data Features

The Big Data has the following features:

Volume: The volume of the data determines the value and potential information of the data under consideration;
Variety: Variety of data types;
Velocity: Velocity that data is obtained;
Variability: Hinder the process of processing and effectively managing data;
Veracity: Data quality;
Complexity: The amount of data is huge, and the sources are multi-channel;
Value: Use big data wisely to create high value at low cost;

Big Data Structure

Big data includes structured, semi-structured, and unstructured data. Unstructured data is increasingly becoming a major part of data. According to the IDC survey report: 80% of the data in the enterprise is unstructured data, and these data increase exponentially by 60% every year.

Big data is just a kind of appearance or characteristic of the Internet development to the present stage, there is no need to myth it or keep it in awe. Big data is set off against the backdrop of technological innovation represented by cloud computing, and these data that originally seemed difficult to collect and use are beginning to be easily utilized. Through continuous innovation in all walks of life, big data will gradually create more value for mankind.

Big Data Application

  • The Los Angeles Police Department and the University of California collaborated to use big data to predict crime;
  • Google Flu Trends uses search keywords to predict the spread of bird flu;
  • MIT uses mobile phone location data and traffic data to build city plans;
  • According to demand and inventory, the Mecy's Department store SAS-based system adjusts prices of up to 73 million items in real time.
  • The medical industry has long encountered the challenge of massive data and unstructured data. In recent years, many countries have actively promoted the development of medical informatization, which makes many medical institutions have funds to do big data analysis.

Big Data Trend

Big Data Trend 1: Data resource utilization

It means that big data has become an important strategic resource that enterprises and society pay attention to, and it has become a new focus that everyone is vying for. Therefore, companies must formulate big data marketing strategic plans in advance to seize market opportunities.

Big Data Trend 2: Deep integration with cloud computing

Big data is inseparable from cloud processing, which provides flexible and expandable basic equipment for big data, and is one of the platforms for generating big data. Since 2013, big data technology has begun to be closely integrated with cloud computing technology, and it is expected that the relationship between the two will be closer in the future. In addition, emerging computing forms such as the Internet of Things and mobile Internet will help the big data revolution together, allowing big data marketing to exert greater influence.

Big Data Trend 3: Breakthrough in scientific theory

With the rapid development of big data, big data is likely to be a new round of technological revolution, just like computers and the Internet. The subsequent emergence of related technologies such as data mining, machine learning, and artificial intelligence may change many algorithms and basic theories in the data world and achieve breakthroughs in science and technology.

Big Data Trend 4: The establishment of data science and data alliance

In the future, data science will become a specialized subject, which will be recognized by more and more people. Major colleges and universities will set up special data science majors, and will also generate a number of new jobs related to them. At the same time, based on the basic platform of data, a cross-domain data sharing platform will also be established. Later, data sharing will extend to the enterprise level and become a core part of the future industry.

Big Data Trend 5: Data breaches are rampant

The growth rate of data breaches in the next few years may reach 100%, unless the data can be secured at its source. It can be said that in the future, every Fortune 500 company will face data attacks, regardless of whether they have taken security precautions. And all companies, regardless of size, need to re-examine today's definition of security. More than 50% of Fortune 500 companies will set up the position of Chief Information Security Officer. Enterprises need to ensure their own and customer data from a new perspective. All data needs to be secured at the beginning of its creation, not in the last link of data storage. Merely strengthening the latter’s security measures has proven to be useless.

Big Data Trend 6: Data management becomes core competitiveness

Data management has become a core competitiveness and directly affects financial performance. When the concept of "data assets are the core assets of an enterprise" became popular, enterprises have a clearer definition of data management. Data management is regarded as the core competitiveness of the enterprise, sustainable development, strategic planning and use of data assets become enterprise data The core of management. The efficiency of data asset management is significantly positively correlated with the growth rate of main business income and sales revenue; in addition, for companies with Internet thinking, the competitiveness of data assets accounts for 36.8%, and the management effect of data assets will directly affect The financial performance of the business.

Big Data Trend 7: Data quality is the key to the success of BI (Business Intelligence)

Companies that use self-service business intelligence tools for big data processing will stand out. One of the challenges is that many data sources will bring a lot of low-quality data. To be successful, companies need to understand the gap between raw data and data analysis, so as to eliminate low-quality data and get better decisions through BI.

Big Data Trend 8: The degree of compounding of the data ecosystem is strengthened

The world of big data is not just a single, huge computer network, but an ecosystem composed of a large number of active components and multiple participant elements. Terminal equipment providers, infrastructure providers, network service providers, network access Into the ecosystem constructed by a series of participants such as service providers, data service enablers, data service providers, touch point services, data service retailers, etc. Today, the basic embryonic form of such a data ecosystem has been formed, and the next development will tend towards the segmentation of the internal roles of the system, that is, the segmentation of the market; the adjustment of system mechanisms, that is, the innovation of business models; Adjustment, that is, the adjustment of the competitive environment, etc., has gradually increased the degree of complexity of the data ecosystem.

The views expressed herein are for reference only and don't necessarily represent the official views of Alibaba Cloud.

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